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At least 37 records · Page 2

The NREL Sensor Laboratory Detection of Hydrogen Emissions

The development of a functional hydrogen detection system is a multifaceted process that integrates hardware, deployments strategies, and analytics which can be supported by the NREL Sensor Laboratory: 1. Support of the design, validation and optimization of sensing prototypes; 2. Guide optimized sensing element development, including control electronics; 3. Laboratory testing to validate/optimize metrological performance (measurement range, detection limit, etc.); 4. Provide test sites for field deployments representative of real-world scenarios with controlled hydrogen releases; 5. Develop sensor placement and operation guidance; 6. Provide guidance on electronics to accommodate facility integration; 7. Electrical safety designs to allow for operation within restricted zones; 8. Integration into facility monitoring and control systems; 9. Guide incorporation of cyber security elements to protect facilities from malicious attacks; 10. Modeling and application of advanced analytics to detect and quantify emissions; 11. Higher Order dispersion models to guide sensor placement for reliable detection; 12. Advanced analytics for improved metrological performances, and to inform inverse modeling; 13. Market support and commercialization (national and international markets); 14. Commercial deployments in H2@SCALE markets (e.g., HUBs and other large-scale hydrogen markets); and 15. Leverage off international collaborations/partnerships (e.g., NREL is on the advisory board for the European initiative "pre-Normative Research on Hydrogen Releases Assessment"-NHyRA).

08 HYDROGEN

Bridging Cloud and Edge Computing at NREL Using CONNECT: Cloud Optimized Networking for Next-Gen Edge Computing Technologies [Slides]

CONNECT is an innovative on-premise hardware and software solution that integrates edge and cloud computing infrastructure at NREL. Built on the AWS Greengrass middleware and leveraging the MQTT protocol, CONNECT enables real-time data streaming from IoT devices and gateways to both cloud and local services, empowering researchers to rapidly capture, analyze, and act upon edge-generated data while leveraging cloud capabilities. The platform addresses research infrastructure challenges by providing a pre-approved platform which is already configured with the correct networking and cybersecurity baselines thus eliminating procurement delays and enabling on-demand availability. CONNECT's hybrid architecture efficiently manages burstable workloads, allowing research teams to dynamically scale computational capacity, handle peak data loads, and reduce operational bottlenecks. Advanced capabilities include built-in GPU support for executing machine learning models which enables low-latency inference at the edge from models trained in the cloud. This architecture supports real-time analytics and filtering, providing a mechanism to allow only transmitting and processing high-value data. Cloud-based configuration management permits engineers to manage on-premise systems remotely, optimizing operational efficiency. By bridging edge and cloud computing, CONNECT provides NREL researchers with a flexible, scalable platform that accelerates scientific discovery while maintaining robust security and performance standards.

97 MATHEMATICS AND COMPUTING

Hydrogen R&D at NREL

This presentation provides an overview of the hydrogen R&D activities at NREL, including make, store, move, and use hydrogen. At NREL, our research spans the advanced water splitting materials (AWSM) and hydrogen storage R&D, performed within the HydroGEN and HyMARC Energy Materials Networks (EMN), respectively, to the materials integration and scale up work done within the H2NEW consortium, to fuel cell R&D within the M2FCT consortium, to stack and systems testing at the MW-level. These R&D activities are funded by U.S. Department of Energy Hydrogen and Fuel Cell Technologies Office.

08 HYDROGEN

WAP Innovation and Collaboration: Updates from NREL

The National Renewable Energy Laboratory (NREL) gives an update on initiatives supporting the Weatherization Assistance Program (WAP). This presentation explains how to leverage NREL's cutting-edge resources, tools, and workforce initiatives to strengthen organizations' impact within the WAP network.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION,

Transforming Energy Through Computational Excellence: NREL's Computational Science Center

Computational methods underpin advancing the science and engineering of energy efficiency, sustainable transportation, renewable power technologies, and developing a knowledge base to optimize energy systems. NREL's Computational Science Center (CSC) proudly focuses on providing the service of computing, advancing the science of computing, and enabling NREL's clean energy mission.

applied mathematics

NREL is Delivering Integrated Solutions for an Affordable and Secure Energy Future

The National Renewable Energy Laboratory (NREL) is the U.S. Department of Energy's primary national laboratory for energy systems research and development. As the energy systems laboratory, NREL's unique strength lies in developing and integrating a broad array of energy technologies into robust, resilient systems - bridging foundational research with practical applications to lower energy costs, drive economic growth, bolster national security, and deliver abundant and reliable energy.

29 ENERGY PLANNING, POLICY, AND ECONOMY

NREL Is Strengthening the Future of Hydropower, A Cornerstone of America's Energy System

The National Renewable Energy Laboratory (NREL) is a leader in advancing hydropower technologies, positioning hydropower as a pillar of an affordable, reliable, and secure energy future. Through its hydropower program, NREL is conducting innovative research that reduces energy costs, drives efficiency, and supports systems integration - unlocking economic opportunities, rebuilding supply chains, and fueling America's global competitiveness.

13 HYDRO ENERGY

Enabling Evaluation of a Southern Company Distribution Feeder on NREL ADMS Test Bed: Cooperative Research and Development (Final Report)

The objective of this project is to enable evaluation of a Southern Company distribution feeder on the Advanced Distribution Management System (ADMS) test bed. The long-term goal is to evaluate a federated distributed energy resource (DER) management solution that aggregates DERs through either direct control, transactive control or an aggregator to provide bulk services while observing distribution system voltage and power constraints. The DER aggregation needs to be coordinated with an ADMS that is responsible for reliable power delivery across the distribution systems. This project takes the first step towards enabling such evaluation by deploying an ADMS from Oracle (Southern Company's ADMS supplier) with a Southern Company feeder at NREL.

24 POWER TRANSMISSION AND DISTRIBUTION

WFIP3 - BARG site - NREL Scanning Lidar (Halo XR+ #235) / Raw Data

These data include raw scanning Doppler lidar measurements from the deployment of the NREL Halo XR+ (s/n 235) at WFIP3's BARG. The raw measurements include uncalibrated beam azimuth angles, radial velocity, backscatter, signal to noise ratio per each line of sight, and range-gate. Note: the measurements have NOT been corrected for the motion of the barge.

17 WIND ENERGY

WFIP3 - BARG site - NREL Profiling Lidar (Windcube v2.1) / Raw Data

This dataset contains raw data from NREL's profiling lidar (Windcube v2.1) at the WFIP3 BARG site. Two data types are included here: 1) STA files, which have 10-minute average data, and 2) RTD files, which have real time data, at about 1 Hz resolution. Note: these data have NOT been corrected for the motion of the barge.

17 WIND ENERGY

NOAA ship - NREL Scanning Lidar (Halo XR #235) / Raw Data

These data include raw scanning Doppler lidar measurements from the deployment of the NREL Halo XR+ (s/n 235) at WFIP3's NOAA ship. The raw measurements include uncalibrated beam azimuth angles, radial velocity, backscatter, signal to noise ratio per each line of sight, and range-gate. The location of the ship is provided separately.

17 WIND ENERGY

WFIP3 - BARG site - NREL Profiling Lidar (Windcube v2.1) / Raw Data

This dataset contains raw data from NREL's profiling lidar (Windcube v2.1) at the WFIP3 NOAA SHIP site. Two data types are included here: 1) STA files, which have 10-minute average data, and 2) RTD files, which have real time data, at about 1 Hz resolution.

17 WIND ENERGY

AWAKEN Site A1 - NREL Scanning Lidar (Halo XR+ #235) / Raw data

These data include raw scanning Doppler lidar measurements from the deployment of the NREL HALO XR+ (s/n 235) at the A1 site. The raw measurements include uncalibrated beam azimuth angles, radial velocity, backscatter, signal to noise ratio per each line of sight, and range-gate.

17 WIND ENERGY

NWTC Site 4.0 - NREL ASSIST (SN10) / Thermodynamic retrievals TROPoe

This dataset contains daily files with thermodynamic profiles retrieved with the optimal estimation physical retrieval TROPoe v0.12 (Turner and Löhnert 2014; Turner and Blumberg 2019; Turner and Löhnert 2021). The profiles are retrieved every 10 minutes from instantaneous observations from the NREL ASSIST-II (SN 10) infrared spectrometer. Observations are noise-filtered but not averaged in time to minimize errors due to non-uniform clouds. Additional input data in TROPoe are cloud base height from a Vaisala CL51 ceilometer. The full pipeline for running the retrieval is available at https://github.com/StefanoWind/TROPoe_processor. Met data were not ingested. In addition to these temporally resolved input data, TROPoe requires an a priori dataset (prior) that provides mean climatological estimates of thermodynamic profiles and specifies how temperature and humidity covary with height as an input (for details see, e.g., Djalalova et al. 2022). The prior is a key component of the retrieval and provides a constraint on the ill-posed inversion problem. A monthly prior was computed from operational radiosonde launches at Denver, CO.

17 WIND ENERGY